Currently, the most common method for inspecting essentially spherical objects (such as fruits and vegetables) requires production line personnel to visually inspect the objects as the objects are conveyed along a production line. However, the human visual inspection process is both slow and unreliable, and some contaminating materials that pose serious health risks are hard to visually identify—particularly on a moving production line. Further, inspectors do not systematically rotate each individual object so that all surfaces of the inspected object are visible to the inspector.
To address these vulnerabilities, fruit and vegetable processors are developing machine vision systems to identify defects and contaminants. One example of such a system is disclosed in U.S. Pat. No. 7,787,111 to Kim et al. (hereinafter “Kim”), which is hereby incorporated by reference. The system disclosed by Kim comprises a rapid online line-scan imaging system capable of both hyperspectral/multispectral reflectance and fluorescence imaging. Reflectance imaging at multiple wavelengths detects quality and surface anomalies, while fluorescence imaging at multiple wavelengths is used to detect fecal matter and other types of bacterial contamination.
Although these examination tools and techniques improve the inspection process, the imaging systems are complex and expensive. For example, in accordance with Kim, multiple cameras may be required to adequately inspect all surfaces of a spheroid. Further, the data collected from all cameras must be processed and synchronized to accurately portray the three-dimensional spheroidal object. For maximum efficiency and minimal error, synchronization and processing should occur almost immediately to ensure that defective objects are not comingled with non-defective items.
The method and apparatus described herein simplifies the imaging process by providing an imaging system that utilises only one camera and associated processor. The system quickly and effectively gathers the imaging data for the whole surface of an inspected object and allows for the identification of essentially all surface defects as well as selected types of bacterial (fecal) contamination.